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numerical analysis, computational fluid dynamics, and uncertainty quantification with diverse applications. Our group maintains active collaborations with other divisions at Linköping University and broader
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for Postdoctoral Associate positions in the broad research areas of mathematical analysis and partial differential equations (PDEs). While all applicants with a background in the analysis of PDEs will be considered
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) Laboratory in the Department of Pathology at University of Colorado Denver. The MT will be involved in various laboratory procedures including analysis of clinical samples by molecular biology methods with a
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Description PhD Student (f/m/d) EU MSCA-Doctorate Network COMBINE: Experimental analysis and simulation of flow-induced vibration in gas-liquid two-phase flow With cutting-edge research in
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simulation. A significant part of the work will involve scientific programming, development of numerical methods, and in-depth physical analysis of flow phenomena. The ideal candidate is passionate about new
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other source documents and entering it into an Electronic Data Capture (EDC).May be responsible for numerous research trials simultaneously. Helps ensure the accurate collection of study- required
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on the candidate’s interests, the project may include field investigations (e.g., paleoseismological trenching, sediment core analysis) and/or numerical modeling of tectonic–erosion–sedimentation interactions. Where
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 15 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09839 Requirements Skills/Qualifications Strong mathematical background. Knowledge in numerical optimization is a plus. Good programming skills in
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of numerical modelling, data processing/analysis, technical report writing, and continuous development of CMAR’s client base under the guidance of CMAR’s Senior Research Consultants and academics. You will
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mangament in numerical models, including advanced calibration strategies from data (observations, measurements, other model predictions) and uncertainty reduction. Scientific context Many engineering and